Overview

Dataset statistics

Number of variables15
Number of observations2115
Missing cells1574
Missing cells (%)5.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory320.7 KiB
Average record size in memory155.2 B

Variable types

Numeric4
Text8
Categorical3

Alerts

perfume_id is highly overall correlated with category and 2 other fieldsHigh correlation
customer_rating is highly overall correlated with review_countHigh correlation
review_count is highly overall correlated with customer_ratingHigh correlation
category is highly overall correlated with perfume_idHigh correlation
gender is highly overall correlated with perfume_idHigh correlation
fragrance is highly overall correlated with perfume_idHigh correlation
top_note has 35 (1.7%) missing valuesMissing
heart_note has 45 (2.1%) missing valuesMissing
base_note has 38 (1.8%) missing valuesMissing
fragrance has 1456 (68.8%) missing valuesMissing
perfume_id has unique valuesUnique
url has unique valuesUnique
image has unique valuesUnique
customer_rating has 841 (39.8%) zerosZeros
review_count has 841 (39.8%) zerosZeros

Reproduction

Analysis started2023-07-27 10:28:05.068291
Analysis finished2023-07-27 10:28:31.960519
Duration26.89 seconds
Software versionydata-profiling vv4.3.2
Download configurationconfig.json

Variables

perfume_id
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct2115
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean79794.049
Minimum11046
Maximum123810
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size97.6 KiB
2023-07-27T12:28:32.158743image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Quantile statistics

Minimum11046
5-th percentile15423.1
Q147579.5
median91489
Q3110644.5
95-th percentile122055.3
Maximum123810
Range112764
Interquartile range (IQR)63065

Descriptive statistics

Standard deviation35688.391
Coefficient of variation (CV)0.4472563
Kurtosis-1.0267733
Mean79794.049
Median Absolute Deviation (MAD)23997
Skewness-0.58568431
Sum1.6876441 × 108
Variance1.2736613 × 109
MonotonicityNot monotonic
2023-07-27T12:28:32.436576image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
12855 1
 
< 0.1%
16157 1
 
< 0.1%
92047 1
 
< 0.1%
105764 1
 
< 0.1%
109064 1
 
< 0.1%
22819 1
 
< 0.1%
121387 1
 
< 0.1%
50559 1
 
< 0.1%
65998 1
 
< 0.1%
65991 1
 
< 0.1%
Other values (2105) 2105
99.5%
ValueCountFrequency (%)
11046 1
< 0.1%
11063 1
< 0.1%
11073 1
< 0.1%
11081 1
< 0.1%
11088 1
< 0.1%
11092 1
< 0.1%
11095 1
< 0.1%
11266 1
< 0.1%
11348 1
< 0.1%
11349 1
< 0.1%
ValueCountFrequency (%)
123810 1
< 0.1%
123748 1
< 0.1%
123720 1
< 0.1%
123614 1
< 0.1%
123613 1
< 0.1%
123542 1
< 0.1%
123541 1
< 0.1%
123432 1
< 0.1%
123422 1
< 0.1%
123413 1
< 0.1%

brand
Text

Distinct238
Distinct (%)11.3%
Missing0
Missing (%)0.0%
Memory size97.6 KiB
2023-07-27T12:28:32.775286image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Length

Max length28
Median length21
Mean length10.158865
Min length3

Characters and Unicode

Total characters21486
Distinct characters69
Distinct categories6 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique40 ?
Unique (%)1.9%

Sample

1st rowHugo Boss
2nd rowYves Saint Laurent
3rd rowAbercrombie & Fitch
4th rowJean Paul Gaultier
5th rowDIOR
ValueCountFrequency (%)
montale 102
 
3.0%
xerjoff 66
 
1.9%
61
 
1.8%
parfums 53
 
1.6%
de 52
 
1.5%
guerlain 46
 
1.4%
dior 46
 
1.4%
maison 36
 
1.1%
acqua 33
 
1.0%
amouage 32
 
0.9%
Other values (353) 2880
84.5%
2023-07-27T12:28:33.157139image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
a 1914
 
8.9%
e 1682
 
7.8%
r 1352
 
6.3%
1292
 
6.0%
i 1228
 
5.7%
n 1075
 
5.0%
o 1072
 
5.0%
s 899
 
4.2%
l 807
 
3.8%
t 647
 
3.0%
Other values (59) 9518
44.3%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 14241
66.3%
Uppercase Letter 5617
 
26.1%
Space Separator 1292
 
6.0%
Other Punctuation 179
 
0.8%
Decimal Number 150
 
0.7%
Dash Punctuation 7
 
< 0.1%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
a 1914
13.4%
e 1682
11.8%
r 1352
9.5%
i 1228
8.6%
n 1075
 
7.5%
o 1072
 
7.5%
s 899
 
6.3%
l 807
 
5.7%
t 647
 
4.5%
u 571
 
4.0%
Other values (20) 2994
21.0%
Uppercase Letter
ValueCountFrequency (%)
M 499
 
8.9%
E 479
 
8.5%
A 393
 
7.0%
R 389
 
6.9%
C 364
 
6.5%
B 342
 
6.1%
P 290
 
5.2%
O 273
 
4.9%
L 267
 
4.8%
N 259
 
4.6%
Other values (15) 2062
36.7%
Decimal Number
ValueCountFrequency (%)
1 69
46.0%
4 19
 
12.7%
7 18
 
12.0%
6 14
 
9.3%
5 12
 
8.0%
2 9
 
6.0%
9 5
 
3.3%
0 4
 
2.7%
Other Punctuation
ValueCountFrequency (%)
. 80
44.7%
& 75
41.9%
' 16
 
8.9%
! 8
 
4.5%
Space Separator
ValueCountFrequency (%)
1292
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 7
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 19858
92.4%
Common 1628
 
7.6%

Most frequent character per script

Latin
ValueCountFrequency (%)
a 1914
 
9.6%
e 1682
 
8.5%
r 1352
 
6.8%
i 1228
 
6.2%
n 1075
 
5.4%
o 1072
 
5.4%
s 899
 
4.5%
l 807
 
4.1%
t 647
 
3.3%
u 571
 
2.9%
Other values (45) 8611
43.4%
Common
ValueCountFrequency (%)
1292
79.4%
. 80
 
4.9%
& 75
 
4.6%
1 69
 
4.2%
4 19
 
1.2%
7 18
 
1.1%
' 16
 
1.0%
6 14
 
0.9%
5 12
 
0.7%
2 9
 
0.6%
Other values (4) 24
 
1.5%

Most occurring blocks

ValueCountFrequency (%)
ASCII 21385
99.5%
None 101
 
0.5%

Most frequent character per block

ASCII
ValueCountFrequency (%)
a 1914
 
9.0%
e 1682
 
7.9%
r 1352
 
6.3%
1292
 
6.0%
i 1228
 
5.7%
n 1075
 
5.0%
o 1072
 
5.0%
s 899
 
4.2%
l 807
 
3.8%
t 647
 
3.0%
Other values (54) 9417
44.0%
None
ValueCountFrequency (%)
é 51
50.5%
è 21
20.8%
ô 19
 
18.8%
ï 6
 
5.9%
ó 4
 
4.0%

name
Text

Distinct1917
Distinct (%)90.6%
Missing0
Missing (%)0.0%
Memory size97.6 KiB
2023-07-27T12:28:33.449736image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Length

Max length63
Median length47
Mean length18.669976
Min length1

Characters and Unicode

Total characters39487
Distinct characters102
Distinct categories17 ?
Distinct scripts3 ?
Distinct blocks4 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1785 ?
Unique (%)84.4%

Sample

1st rowBOSS Bottled
2nd rowY
3rd rowAway Weekend Men
4th rowLe Mâle
5th rowSauvage Citrus and Vanilla Notes
ValueCountFrequency (%)
collection 297
 
4.6%
the 113
 
1.8%
les 102
 
1.6%
de 91
 
1.4%
oud 79
 
1.2%
homme 73
 
1.1%
for 70
 
1.1%
rose 57
 
0.9%
men 56
 
0.9%
pour 50
 
0.8%
Other values (1914) 5421
84.6%
2023-07-27T12:28:34.107362image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
4294
 
10.9%
e 3766
 
9.5%
o 2800
 
7.1%
i 2371
 
6.0%
a 2340
 
5.9%
n 2096
 
5.3%
l 2030
 
5.1%
r 1927
 
4.9%
s 1675
 
4.2%
t 1524
 
3.9%
Other values (92) 14664
37.1%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 27595
69.9%
Uppercase Letter 6825
 
17.3%
Space Separator 4294
 
10.9%
Decimal Number 370
 
0.9%
Other Punctuation 310
 
0.8%
Dash Punctuation 45
 
0.1%
Final Punctuation 14
 
< 0.1%
Other Symbol 13
 
< 0.1%
Math Symbol 5
 
< 0.1%
Modifier Symbol 5
 
< 0.1%
Other values (7) 11
 
< 0.1%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
e 3766
13.6%
o 2800
10.1%
i 2371
8.6%
a 2340
8.5%
n 2096
 
7.6%
l 2030
 
7.4%
r 1927
 
7.0%
s 1675
 
6.1%
t 1524
 
5.5%
u 1248
 
4.5%
Other values (30) 5818
21.1%
Uppercase Letter
ValueCountFrequency (%)
C 686
 
10.1%
L 486
 
7.1%
S 483
 
7.1%
M 442
 
6.5%
O 388
 
5.7%
E 385
 
5.6%
A 355
 
5.2%
B 354
 
5.2%
F 342
 
5.0%
I 338
 
5.0%
Other values (19) 2566
37.6%
Decimal Number
ValueCountFrequency (%)
1 111
30.0%
2 69
18.6%
0 41
 
11.1%
8 36
 
9.7%
3 26
 
7.0%
9 25
 
6.8%
5 17
 
4.6%
4 16
 
4.3%
7 15
 
4.1%
6 14
 
3.8%
Other Punctuation
ValueCountFrequency (%)
' 181
58.4%
. 70
 
22.6%
& 35
 
11.3%
! 11
 
3.5%
% 8
 
2.6%
, 3
 
1.0%
* 1
 
0.3%
/ 1
 
0.3%
Math Symbol
ValueCountFrequency (%)
| 4
80.0%
+ 1
 
20.0%
Modifier Symbol
ValueCountFrequency (%)
´ 3
60.0%
` 2
40.0%
Space Separator
ValueCountFrequency (%)
4294
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 45
100.0%
Final Punctuation
ValueCountFrequency (%)
’ 14
100.0%
Other Symbol
ValueCountFrequency (%)
° 13
100.0%
Initial Punctuation
ValueCountFrequency (%)
‘ 4
100.0%
Currency Symbol
ValueCountFrequency (%)
$ 2
100.0%
Nonspacing Mark
ValueCountFrequency (%)
ÌŠ 1
100.0%
Other Number
ValueCountFrequency (%)
² 1
100.0%
Close Punctuation
ValueCountFrequency (%)
) 1
100.0%
Open Punctuation
ValueCountFrequency (%)
( 1
100.0%
Connector Punctuation
ValueCountFrequency (%)
_ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 34420
87.2%
Common 5066
 
12.8%
Inherited 1
 
< 0.1%

Most frequent character per script

Latin
ValueCountFrequency (%)
e 3766
 
10.9%
o 2800
 
8.1%
i 2371
 
6.9%
a 2340
 
6.8%
n 2096
 
6.1%
l 2030
 
5.9%
r 1927
 
5.6%
s 1675
 
4.9%
t 1524
 
4.4%
u 1248
 
3.6%
Other values (59) 12643
36.7%
Common
ValueCountFrequency (%)
4294
84.8%
' 181
 
3.6%
1 111
 
2.2%
. 70
 
1.4%
2 69
 
1.4%
- 45
 
0.9%
0 41
 
0.8%
8 36
 
0.7%
& 35
 
0.7%
3 26
 
0.5%
Other values (22) 158
 
3.1%
Inherited
ValueCountFrequency (%)
ÌŠ 1
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 39217
99.3%
None 251
 
0.6%
Punctuation 18
 
< 0.1%
Diacriticals 1
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
4294
 
10.9%
e 3766
 
9.6%
o 2800
 
7.1%
i 2371
 
6.0%
a 2340
 
6.0%
n 2096
 
5.3%
l 2030
 
5.2%
r 1927
 
4.9%
s 1675
 
4.3%
t 1524
 
3.9%
Other values (69) 14394
36.7%
None
ValueCountFrequency (%)
é 132
52.6%
è 26
 
10.4%
É 21
 
8.4%
ê 16
 
6.4%
° 13
 
5.2%
î 11
 
4.4%
ô 6
 
2.4%
ò 5
 
2.0%
â 4
 
1.6%
´ 3
 
1.2%
Other values (10) 14
 
5.6%
Punctuation
ValueCountFrequency (%)
’ 14
77.8%
‘ 4
 
22.2%
Diacriticals
ValueCountFrequency (%)
ÌŠ 1
100.0%

category
Categorical

HIGH CORRELATION 

Distinct5
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size97.6 KiB
Eau de Parfum
1264 
Eau de Toilette
609 
Parfum
195 
Eau de Cologne
 
44
Eau Fraiche
 
3

Length

Max length15
Median length13
Mean length12.948463
Min length6

Characters and Unicode

Total characters27386
Distinct characters21
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowEau de Toilette
2nd rowEau de Parfum
3rd rowEau de Toilette
4th rowEau de Toilette
5th rowEau de Parfum

Common Values

ValueCountFrequency (%)
Eau de Parfum 1264
59.8%
Eau de Toilette 609
28.8%
Parfum 195
 
9.2%
Eau de Cologne 44
 
2.1%
Eau Fraiche 3
 
0.1%

Length

2023-07-27T12:28:34.255468image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-07-27T12:28:34.396733image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
ValueCountFrequency (%)
eau 1920
32.3%
de 1917
32.2%
parfum 1459
24.5%
toilette 609
 
10.2%
cologne 44
 
0.7%
fraiche 3
 
0.1%

Most occurring characters

ValueCountFrequency (%)
3837
14.0%
a 3382
12.3%
u 3379
12.3%
e 3182
11.6%
E 1920
7.0%
d 1917
7.0%
r 1462
 
5.3%
P 1459
 
5.3%
f 1459
 
5.3%
m 1459
 
5.3%
Other values (11) 3930
14.4%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 19514
71.3%
Uppercase Letter 4035
 
14.7%
Space Separator 3837
 
14.0%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
a 3382
17.3%
u 3379
17.3%
e 3182
16.3%
d 1917
9.8%
r 1462
7.5%
f 1459
7.5%
m 1459
7.5%
t 1218
 
6.2%
o 697
 
3.6%
l 653
 
3.3%
Other values (5) 706
 
3.6%
Uppercase Letter
ValueCountFrequency (%)
E 1920
47.6%
P 1459
36.2%
T 609
 
15.1%
C 44
 
1.1%
F 3
 
0.1%
Space Separator
ValueCountFrequency (%)
3837
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 23549
86.0%
Common 3837
 
14.0%

Most frequent character per script

Latin
ValueCountFrequency (%)
a 3382
14.4%
u 3379
14.3%
e 3182
13.5%
E 1920
8.2%
d 1917
8.1%
r 1462
6.2%
P 1459
6.2%
f 1459
6.2%
m 1459
6.2%
t 1218
 
5.2%
Other values (10) 2712
11.5%
Common
ValueCountFrequency (%)
3837
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 27386
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
3837
14.0%
a 3382
12.3%
u 3379
12.3%
e 3182
11.6%
E 1920
7.0%
d 1917
7.0%
r 1462
 
5.3%
P 1459
 
5.3%
f 1459
 
5.3%
m 1459
 
5.3%
Other values (11) 3930
14.4%

gender
Categorical

HIGH CORRELATION 

Distinct3
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size97.6 KiB
Women
885 
Unisex
673 
Men
557 

Length

Max length6
Median length5
Mean length4.7914894
Min length3

Characters and Unicode

Total characters10134
Distinct characters10
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowMen
2nd rowMen
3rd rowMen
4th rowMen
5th rowMen

Common Values

ValueCountFrequency (%)
Women 885
41.8%
Unisex 673
31.8%
Men 557
26.3%

Length

2023-07-27T12:28:34.521846image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-07-27T12:28:34.647435image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
ValueCountFrequency (%)
women 885
41.8%
unisex 673
31.8%
men 557
26.3%

Most occurring characters

ValueCountFrequency (%)
e 2115
20.9%
n 2115
20.9%
W 885
8.7%
o 885
8.7%
m 885
8.7%
U 673
 
6.6%
i 673
 
6.6%
s 673
 
6.6%
x 673
 
6.6%
M 557
 
5.5%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 8019
79.1%
Uppercase Letter 2115
 
20.9%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
e 2115
26.4%
n 2115
26.4%
o 885
11.0%
m 885
11.0%
i 673
 
8.4%
s 673
 
8.4%
x 673
 
8.4%
Uppercase Letter
ValueCountFrequency (%)
W 885
41.8%
U 673
31.8%
M 557
26.3%

Most occurring scripts

ValueCountFrequency (%)
Latin 10134
100.0%

Most frequent character per script

Latin
ValueCountFrequency (%)
e 2115
20.9%
n 2115
20.9%
W 885
8.7%
o 885
8.7%
m 885
8.7%
U 673
 
6.6%
i 673
 
6.6%
s 673
 
6.6%
x 673
 
6.6%
M 557
 
5.5%

Most occurring blocks

ValueCountFrequency (%)
ASCII 10134
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
e 2115
20.9%
n 2115
20.9%
W 885
8.7%
o 885
8.7%
m 885
8.7%
U 673
 
6.6%
i 673
 
6.6%
s 673
 
6.6%
x 673
 
6.6%
M 557
 
5.5%

base_price
Real number (ℝ)

Distinct627
Distinct (%)29.6%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1759.6487
Minimum79.5
Maximum16000
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size97.6 KiB
2023-07-27T12:28:34.771174image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Quantile statistics

Minimum79.5
5-th percentile359
Q1900
median1359
Q32099
95-th percentile4513.831
Maximum16000
Range15920.5
Interquartile range (IQR)1199

Descriptive statistics

Standard deviation1542.2449
Coefficient of variation (CV)0.87645048
Kurtosis19.636206
Mean1759.6487
Median Absolute Deviation (MAD)569.5
Skewness3.4822163
Sum3721657
Variance2378519.5
MonotonicityNot monotonic
2023-07-27T12:28:34.901976image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1250 41
 
1.9%
3450 25
 
1.2%
999.5 23
 
1.1%
1796.67 21
 
1.0%
1050 20
 
0.9%
1350 18
 
0.9%
1331.67 17
 
0.8%
1199 15
 
0.7%
2866.67 15
 
0.7%
1949.5 14
 
0.7%
Other values (617) 1906
90.1%
ValueCountFrequency (%)
79.5 1
 
< 0.1%
84.9 7
0.3%
89.5 1
 
< 0.1%
94.33 11
0.5%
113.2 2
 
0.1%
151.33 1
 
< 0.1%
156.9 1
 
< 0.1%
159.5 3
 
0.1%
161 1
 
< 0.1%
162.65 1
 
< 0.1%
ValueCountFrequency (%)
16000 2
 
0.1%
15000 2
 
0.1%
12530 1
 
< 0.1%
11000 8
0.4%
10800 1
 
< 0.1%
9000 3
 
0.1%
8731.67 4
0.2%
8000 5
0.2%
7200 1
 
< 0.1%
7195 3
 
0.1%

notes
Text

Distinct2054
Distinct (%)97.1%
Missing0
Missing (%)0.0%
Memory size97.6 KiB
2023-07-27T12:28:35.117515image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Length

Max length258
Median length145
Mean length71.725768
Min length4

Characters and Unicode

Total characters151700
Distinct characters32
Distinct categories5 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1997 ?
Unique (%)94.4%

Sample

1st rowapple, bergamot, lemon, geranium, carnation, cinnamon, sandalwood, vetiver, cedar
2nd rowapple, bergamot, ginger, geranium, mint, sage, juniper berry, amber, tonka bean, incense
3rd rowbergamot, cardamom, mandarin, lavender, rosemary, sage, cocoa, patchouli, cedar wood
4th rowbergamot, lavender, mint, spices, orange, cinnamon, amber, sandalwood, tonka bean
5th rowbergamot, lavender, pepper, amber, patchouli, vetiver
ValueCountFrequency (%)
musk 983
 
5.2%
jasmine 760
 
4.0%
bergamot 748
 
4.0%
vanilla 710
 
3.8%
rose 709
 
3.7%
patchouli 695
 
3.7%
sandalwood 661
 
3.5%
cedar 618
 
3.3%
amber 587
 
3.1%
wood 461
 
2.4%
Other values (328) 11982
63.3%
2023-07-27T12:28:35.497260image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
16799
 
11.1%
, 15170
 
10.0%
a 14623
 
9.6%
e 12670
 
8.4%
o 9800
 
6.5%
r 9437
 
6.2%
n 8759
 
5.8%
i 7160
 
4.7%
l 7068
 
4.7%
m 6589
 
4.3%
Other values (22) 43625
28.8%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 119562
78.8%
Space Separator 16799
 
11.1%
Other Punctuation 15170
 
10.0%
Dash Punctuation 168
 
0.1%
Other Symbol 1
 
< 0.1%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
a 14623
12.2%
e 12670
 
10.6%
o 9800
 
8.2%
r 9437
 
7.9%
n 8759
 
7.3%
i 7160
 
6.0%
l 7068
 
5.9%
m 6589
 
5.5%
s 6434
 
5.4%
t 4868
 
4.1%
Other values (18) 32154
26.9%
Space Separator
ValueCountFrequency (%)
16799
100.0%
Other Punctuation
ValueCountFrequency (%)
, 15170
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 168
100.0%
Other Symbol
ValueCountFrequency (%)
® 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 119562
78.8%
Common 32138
 
21.2%

Most frequent character per script

Latin
ValueCountFrequency (%)
a 14623
12.2%
e 12670
 
10.6%
o 9800
 
8.2%
r 9437
 
7.9%
n 8759
 
7.3%
i 7160
 
6.0%
l 7068
 
5.9%
m 6589
 
5.5%
s 6434
 
5.4%
t 4868
 
4.1%
Other values (18) 32154
26.9%
Common
ValueCountFrequency (%)
16799
52.3%
, 15170
47.2%
- 168
 
0.5%
® 1
 
< 0.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 151667
> 99.9%
None 33
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
16799
 
11.1%
, 15170
 
10.0%
a 14623
 
9.6%
e 12670
 
8.4%
o 9800
 
6.5%
r 9437
 
6.2%
n 8759
 
5.8%
i 7160
 
4.7%
l 7068
 
4.7%
m 6589
 
4.3%
Other values (19) 43592
28.7%
None
ValueCountFrequency (%)
é 28
84.8%
è 4
 
12.1%
® 1
 
3.0%

top_note
Text

MISSING 

Distinct1518
Distinct (%)73.0%
Missing35
Missing (%)1.7%
Memory size97.6 KiB
2023-07-27T12:28:35.710669image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Length

Max length185
Median length68
Mean length23.602404
Min length3

Characters and Unicode

Total characters49093
Distinct characters30
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1290 ?
Unique (%)62.0%

Sample

1st rowapple, bergamot, lemon
2nd rowapple, bergamot, ginger
3rd rowbergamot, cardamom, mandarin
4th rowbergamot, lavender, mint
5th rowbergamot, lavender
ValueCountFrequency (%)
bergamot 730
 
11.8%
mandarin 355
 
5.7%
lemon 351
 
5.7%
pepper 313
 
5.0%
orange 245
 
4.0%
grapefruit 197
 
3.2%
cardamom 149
 
2.4%
rose 146
 
2.4%
blackcurrant 144
 
2.3%
apple 123
 
2.0%
Other values (233) 3449
55.6%
2023-07-27T12:28:36.093775image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
e 4991
 
10.2%
a 4756
 
9.7%
r 4350
 
8.9%
4122
 
8.4%
, 3718
 
7.6%
n 3237
 
6.6%
o 2978
 
6.1%
m 2634
 
5.4%
i 2177
 
4.4%
t 2054
 
4.2%
Other values (20) 14076
28.7%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 41219
84.0%
Space Separator 4122
 
8.4%
Other Punctuation 3718
 
7.6%
Dash Punctuation 34
 
0.1%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
e 4991
12.1%
a 4756
11.5%
r 4350
10.6%
n 3237
 
7.9%
o 2978
 
7.2%
m 2634
 
6.4%
i 2177
 
5.3%
t 2054
 
5.0%
p 1998
 
4.8%
l 1905
 
4.6%
Other values (17) 10139
24.6%
Space Separator
ValueCountFrequency (%)
4122
100.0%
Other Punctuation
ValueCountFrequency (%)
, 3718
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 34
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 41219
84.0%
Common 7874
 
16.0%

Most frequent character per script

Latin
ValueCountFrequency (%)
e 4991
12.1%
a 4756
11.5%
r 4350
10.6%
n 3237
 
7.9%
o 2978
 
7.2%
m 2634
 
6.4%
i 2177
 
5.3%
t 2054
 
5.0%
p 1998
 
4.8%
l 1905
 
4.6%
Other values (17) 10139
24.6%
Common
ValueCountFrequency (%)
4122
52.3%
, 3718
47.2%
- 34
 
0.4%

Most occurring blocks

ValueCountFrequency (%)
ASCII 49087
> 99.9%
None 6
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
e 4991
 
10.2%
a 4756
 
9.7%
r 4350
 
8.9%
4122
 
8.4%
, 3718
 
7.6%
n 3237
 
6.6%
o 2978
 
6.1%
m 2634
 
5.4%
i 2177
 
4.4%
t 2054
 
4.2%
Other values (19) 14070
28.7%
None
ValueCountFrequency (%)
é 6
100.0%

heart_note
Text

MISSING 

Distinct1554
Distinct (%)75.1%
Missing45
Missing (%)2.1%
Memory size97.6 KiB
2023-07-27T12:28:36.362475image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Length

Max length165
Median length69
Mean length24.314493
Min length3

Characters and Unicode

Total characters50331
Distinct characters31
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1367 ?
Unique (%)66.0%

Sample

1st rowgeranium, carnation, cinnamon
2nd rowgeranium, mint, sage, juniper berry
3rd rowlavender, rosemary, sage
4th rowspices, orange, cinnamon
5th rowpepper
ValueCountFrequency (%)
jasmine 682
 
10.1%
rose 579
 
8.6%
iris 210
 
3.1%
patchouli 180
 
2.7%
lily 178
 
2.6%
violet 171
 
2.5%
cedar 164
 
2.4%
orange 163
 
2.4%
lavender 143
 
2.1%
geranium 138
 
2.0%
Other values (231) 4130
61.3%
2023-07-27T12:28:36.818115image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
e 5026
 
10.0%
4668
 
9.3%
a 4507
 
9.0%
, 3867
 
7.7%
o 3476
 
6.9%
n 3233
 
6.4%
r 3197
 
6.4%
i 3159
 
6.3%
s 2855
 
5.7%
l 2619
 
5.2%
Other values (21) 13724
27.3%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 41662
82.8%
Space Separator 4668
 
9.3%
Other Punctuation 3867
 
7.7%
Dash Punctuation 134
 
0.3%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
e 5026
12.1%
a 4507
10.8%
o 3476
 
8.3%
n 3233
 
7.8%
r 3197
 
7.7%
i 3159
 
7.6%
s 2855
 
6.9%
l 2619
 
6.3%
m 1998
 
4.8%
t 1471
 
3.5%
Other values (18) 10121
24.3%
Space Separator
ValueCountFrequency (%)
4668
100.0%
Other Punctuation
ValueCountFrequency (%)
, 3867
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 134
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 41662
82.8%
Common 8669
 
17.2%

Most frequent character per script

Latin
ValueCountFrequency (%)
e 5026
12.1%
a 4507
10.8%
o 3476
 
8.3%
n 3233
 
7.8%
r 3197
 
7.7%
i 3159
 
7.6%
s 2855
 
6.9%
l 2619
 
6.3%
m 1998
 
4.8%
t 1471
 
3.5%
Other values (18) 10121
24.3%
Common
ValueCountFrequency (%)
4668
53.8%
, 3867
44.6%
- 134
 
1.5%

Most occurring blocks

ValueCountFrequency (%)
ASCII 50313
> 99.9%
None 18
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
e 5026
 
10.0%
4668
 
9.3%
a 4507
 
9.0%
, 3867
 
7.7%
o 3476
 
6.9%
n 3233
 
6.4%
r 3197
 
6.4%
i 3159
 
6.3%
s 2855
 
5.7%
l 2619
 
5.2%
Other values (19) 13706
27.2%
None
ValueCountFrequency (%)
é 16
88.9%
è 2
 
11.1%

base_note
Text

MISSING 

Distinct1231
Distinct (%)59.3%
Missing38
Missing (%)1.8%
Memory size97.6 KiB
2023-07-27T12:28:37.070456image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Length

Max length174
Median length75
Mean length24.834858
Min length3

Characters and Unicode

Total characters51582
Distinct characters32
Distinct categories5 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique998 ?
Unique (%)48.1%

Sample

1st rowsandalwood, vetiver, cedar
2nd rowamber, tonka bean, incense
3rd rowcocoa, patchouli, cedar wood
4th rowamber, sandalwood, tonka bean
5th rowamber, patchouli, vetiver
ValueCountFrequency (%)
musk 934
13.5%
vanilla 634
 
9.2%
sandalwood 592
 
8.6%
amber 527
 
7.6%
patchouli 514
 
7.4%
cedar 456
 
6.6%
wood 350
 
5.1%
vetiver 322
 
4.7%
bean 256
 
3.7%
tonka 255
 
3.7%
Other values (184) 2075
30.0%
2023-07-27T12:28:37.483781image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
a 6013
 
11.7%
4838
 
9.4%
, 4307
 
8.3%
o 3840
 
7.4%
e 3245
 
6.3%
l 2918
 
5.7%
n 2704
 
5.2%
s 2585
 
5.0%
r 2293
 
4.4%
m 2274
 
4.4%
Other values (22) 16565
32.1%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 42426
82.2%
Space Separator 4838
 
9.4%
Other Punctuation 4307
 
8.3%
Dash Punctuation 10
 
< 0.1%
Other Symbol 1
 
< 0.1%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
a 6013
14.2%
o 3840
 
9.1%
e 3245
 
7.6%
l 2918
 
6.9%
n 2704
 
6.4%
s 2585
 
6.1%
r 2293
 
5.4%
m 2274
 
5.4%
d 2236
 
5.3%
i 2191
 
5.2%
Other values (18) 12127
28.6%
Space Separator
ValueCountFrequency (%)
4838
100.0%
Other Punctuation
ValueCountFrequency (%)
, 4307
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 10
100.0%
Other Symbol
ValueCountFrequency (%)
® 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 42426
82.2%
Common 9156
 
17.8%

Most frequent character per script

Latin
ValueCountFrequency (%)
a 6013
14.2%
o 3840
 
9.1%
e 3245
 
7.6%
l 2918
 
6.9%
n 2704
 
6.4%
s 2585
 
6.1%
r 2293
 
5.4%
m 2274
 
5.4%
d 2236
 
5.3%
i 2191
 
5.2%
Other values (18) 12127
28.6%
Common
ValueCountFrequency (%)
4838
52.8%
, 4307
47.0%
- 10
 
0.1%
® 1
 
< 0.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 51573
> 99.9%
None 9
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
a 6013
 
11.7%
4838
 
9.4%
, 4307
 
8.4%
o 3840
 
7.4%
e 3245
 
6.3%
l 2918
 
5.7%
n 2704
 
5.2%
s 2585
 
5.0%
r 2293
 
4.4%
m 2274
 
4.4%
Other values (19) 16556
32.1%
None
ValueCountFrequency (%)
é 6
66.7%
è 2
 
22.2%
® 1
 
11.1%

fragrance
Categorical

HIGH CORRELATION  MISSING 

Distinct18
Distinct (%)2.7%
Missing1456
Missing (%)68.8%
Memory size97.6 KiB
floral
258 
wooden
105 
oriental
48 
fresh
47 
spicy
39 
Other values (13)
162 

Length

Max length9
Median length6
Mean length6.2898331
Min length5

Characters and Unicode

Total characters4145
Distinct characters23
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1 ?
Unique (%)0.2%

Sample

1st rowwooden
2nd rowwooden
3rd roworiental
4th rowaquatic
5th rowwooden

Common Values

ValueCountFrequency (%)
floral 258
 
12.2%
wooden 105
 
5.0%
oriental 48
 
2.3%
fresh 47
 
2.2%
spicy 39
 
1.8%
arromatic 38
 
1.8%
citrusy 32
 
1.5%
fruity 29
 
1.4%
sweet 10
 
0.5%
amber 10
 
0.5%
Other values (8) 43
 
2.0%
(Missing) 1456
68.8%

Length

2023-07-27T12:28:37.632439image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
floral 258
39.2%
wooden 105
15.9%
oriental 48
 
7.3%
fresh 47
 
7.1%
spicy 39
 
5.9%
arromatic 38
 
5.8%
citrusy 32
 
4.9%
fruity 29
 
4.4%
amber 10
 
1.5%
sweet 10
 
1.5%
Other values (8) 43
 
6.5%

Most occurring characters

ValueCountFrequency (%)
l 576
13.9%
o 575
13.9%
r 531
12.8%
a 428
10.3%
f 343
8.3%
e 265
 
6.4%
i 198
 
4.8%
t 175
 
4.2%
n 163
 
3.9%
s 134
 
3.2%
Other values (13) 757
18.3%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 4145
100.0%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
l 576
13.9%
o 575
13.9%
r 531
12.8%
a 428
10.3%
f 343
8.3%
e 265
 
6.4%
i 198
 
4.8%
t 175
 
4.2%
n 163
 
3.9%
s 134
 
3.2%
Other values (13) 757
18.3%

Most occurring scripts

ValueCountFrequency (%)
Latin 4145
100.0%

Most frequent character per script

Latin
ValueCountFrequency (%)
l 576
13.9%
o 575
13.9%
r 531
12.8%
a 428
10.3%
f 343
8.3%
e 265
 
6.4%
i 198
 
4.8%
t 175
 
4.2%
n 163
 
3.9%
s 134
 
3.2%
Other values (13) 757
18.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 4136
99.8%
None 9
 
0.2%

Most frequent character per block

ASCII
ValueCountFrequency (%)
l 576
13.9%
o 575
13.9%
r 531
12.8%
a 428
10.3%
f 343
8.3%
e 265
 
6.4%
i 198
 
4.8%
t 175
 
4.2%
n 163
 
3.9%
s 134
 
3.2%
Other values (12) 748
18.1%
None
ValueCountFrequency (%)
è 9
100.0%

customer_rating
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct22
Distinct (%)1.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2.8775414
Minimum0
Maximum5
Zeros841
Zeros (%)39.8%
Negative0
Negative (%)0.0%
Memory size97.6 KiB
2023-07-27T12:28:37.821100image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median4.6
Q35
95-th percentile5
Maximum5
Range5
Interquartile range (IQR)5

Descriptive statistics

Standard deviation2.3704926
Coefficient of variation (CV)0.82379097
Kurtosis-1.8326844
Mean2.8775414
Median Absolute Deviation (MAD)0.4
Skewness-0.36312603
Sum6086
Variance5.6192352
MonotonicityNot monotonic
2023-07-27T12:28:38.013946image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
Histogram with fixed size bins (bins=22)
ValueCountFrequency (%)
0 841
39.8%
5 713
33.7%
4.9 148
 
7.0%
4.8 106
 
5.0%
4.7 83
 
3.9%
4 44
 
2.1%
4.5 41
 
1.9%
4.6 31
 
1.5%
4.4 24
 
1.1%
4.2 21
 
1.0%
Other values (12) 63
 
3.0%
ValueCountFrequency (%)
0 841
39.8%
1 9
 
0.4%
2 5
 
0.2%
2.5 1
 
< 0.1%
2.7 1
 
< 0.1%
3 12
 
0.6%
3.4 2
 
0.1%
3.5 3
 
0.1%
3.7 4
 
0.2%
3.8 5
 
0.2%
ValueCountFrequency (%)
5 713
33.7%
4.9 148
 
7.0%
4.8 106
 
5.0%
4.7 83
 
3.9%
4.6 31
 
1.5%
4.5 41
 
1.9%
4.4 24
 
1.1%
4.3 14
 
0.7%
4.2 21
 
1.0%
4.1 6
 
0.3%

review_count
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct154
Distinct (%)7.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean17.30922
Minimum0
Maximum2989
Zeros841
Zeros (%)39.8%
Negative0
Negative (%)0.0%
Memory size89.3 KiB
2023-07-27T12:28:38.203933image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median1
Q36
95-th percentile77.3
Maximum2989
Range2989
Interquartile range (IQR)6

Descriptive statistics

Standard deviation95.339868
Coefficient of variation (CV)5.5080396
Kurtosis498.68708
Mean17.30922
Median Absolute Deviation (MAD)1
Skewness18.911242
Sum36609
Variance9089.6905
MonotonicityNot monotonic
2023-07-27T12:28:38.397733image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 841
39.8%
1 299
 
14.1%
2 179
 
8.5%
3 114
 
5.4%
4 81
 
3.8%
5 58
 
2.7%
6 45
 
2.1%
8 44
 
2.1%
7 37
 
1.7%
9 32
 
1.5%
Other values (144) 385
18.2%
ValueCountFrequency (%)
0 841
39.8%
1 299
 
14.1%
2 179
 
8.5%
3 114
 
5.4%
4 81
 
3.8%
5 58
 
2.7%
6 45
 
2.1%
7 37
 
1.7%
8 44
 
2.1%
9 32
 
1.5%
ValueCountFrequency (%)
2989 1
< 0.1%
1502 1
< 0.1%
1204 1
< 0.1%
1083 1
< 0.1%
843 1
< 0.1%
688 1
< 0.1%
662 1
< 0.1%
619 1
< 0.1%
510 1
< 0.1%
480 1
< 0.1%

url
Text

UNIQUE 

Distinct2115
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size97.6 KiB
2023-07-27T12:28:38.715720image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Length

Max length110
Median length95
Mean length78.410875
Min length53

Characters and Unicode

Total characters165839
Distinct characters68
Distinct categories7 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique2115 ?
Unique (%)100.0%

Sample

1st row/Hugo-Boss/Boss-Black-Mens-fragrances/BOSS-Bottled/Eau-de-Toilette-Spray/index_12855.aspx
2nd row/Yves-Saint-Laurent/Mens-fragrances/Y/Eau-de-Parfum-Spray/index_79931.aspx
3rd row/Abercrombie-Fitch/Mens-fragrances/Away-Weekend-Men/Eau-de-Toilette-Spray/index_123613.aspx
4th row/Jean-Paul-Gaultier/Mens-fragrances/Le-Male/Eau-de-Toilette-Spray/index_17304.aspx
5th row/DIOR/Mens-fragrances/Sauvage/Eau-de-Parfum-Spray/index_74836.aspx
ValueCountFrequency (%)
hugo-boss/boss-black-mens-fragrances/boss-bottled/eau-de-toilette-spray/index_12855.aspx 1
 
< 0.1%
dior/mens-fragrances/fahrenheit/le-parfum-spray/index_44912.aspx 1
 
< 0.1%
abercrombie-fitch/mens-fragrances/away-weekend-men/eau-de-toilette-spray/index_123613.aspx 1
 
< 0.1%
jean-paul-gaultier/mens-fragrances/le-male/eau-de-toilette-spray/index_17304.aspx 1
 
< 0.1%
dior/mens-fragrances/sauvage/eau-de-parfum-spray/index_74836.aspx 1
 
< 0.1%
jil-sander/mens-fragrances/sun-men/eau-de-toilette-spray/index_17427.aspx 1
 
< 0.1%
gisada/mens-fragrances/ambassador-for-men/eau-de-parfum-spray/index_94968.aspx 1
 
< 0.1%
paco-rabanne/mens-fragrances/1-million/eau-de-toilette-spray/index_13455.aspx 1
 
< 0.1%
paco-rabanne/mens-fragrances/1-million/parfum-spray/index_90243.aspx 1
 
< 0.1%
creed/mens-fragrances/aventus/eau-de-parfum-spray/index_29150.aspx 1
 
< 0.1%
Other values (2105) 2105
99.5%
2023-07-27T12:28:39.247266image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
a 14421
 
8.7%
e 13778
 
8.3%
- 11370
 
6.9%
/ 10575
 
6.4%
r 9673
 
5.8%
n 8390
 
5.1%
s 7729
 
4.7%
i 6498
 
3.9%
o 5434
 
3.3%
d 5056
 
3.0%
Other values (58) 72915
44.0%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 108916
65.7%
Uppercase Letter 19026
 
11.5%
Other Punctuation 12708
 
7.7%
Decimal Number 11702
 
7.1%
Dash Punctuation 11370
 
6.9%
Connector Punctuation 2115
 
1.3%
Currency Symbol 2
 
< 0.1%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
a 14421
13.2%
e 13778
12.7%
r 9673
 
8.9%
n 8390
 
7.7%
s 7729
 
7.1%
i 6498
 
6.0%
o 5434
 
5.0%
d 5056
 
4.6%
u 4832
 
4.4%
x 4791
 
4.4%
Other values (16) 28314
26.0%
Uppercase Letter
ValueCountFrequency (%)
E 2802
14.7%
S 2471
13.0%
P 1980
 
10.4%
C 1350
 
7.1%
M 1299
 
6.8%
T 1044
 
5.5%
W 954
 
5.0%
L 676
 
3.6%
F 672
 
3.5%
A 641
 
3.4%
Other values (16) 5137
27.0%
Decimal Number
ValueCountFrequency (%)
1 2266
19.4%
2 1161
9.9%
9 1140
9.7%
4 1083
9.3%
6 1082
9.2%
8 1048
9.0%
0 1013
8.7%
3 1010
8.6%
7 1002
8.6%
5 897
 
7.7%
Other Punctuation
ValueCountFrequency (%)
/ 10575
83.2%
. 2115
 
16.6%
! 18
 
0.1%
Dash Punctuation
ValueCountFrequency (%)
- 11370
100.0%
Connector Punctuation
ValueCountFrequency (%)
_ 2115
100.0%
Currency Symbol
ValueCountFrequency (%)
$ 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 127942
77.1%
Common 37897
 
22.9%

Most frequent character per script

Latin
ValueCountFrequency (%)
a 14421
 
11.3%
e 13778
 
10.8%
r 9673
 
7.6%
n 8390
 
6.6%
s 7729
 
6.0%
i 6498
 
5.1%
o 5434
 
4.2%
d 5056
 
4.0%
u 4832
 
3.8%
x 4791
 
3.7%
Other values (42) 47340
37.0%
Common
ValueCountFrequency (%)
- 11370
30.0%
/ 10575
27.9%
1 2266
 
6.0%
. 2115
 
5.6%
_ 2115
 
5.6%
2 1161
 
3.1%
9 1140
 
3.0%
4 1083
 
2.9%
6 1082
 
2.9%
8 1048
 
2.8%
Other values (6) 3942
 
10.4%

Most occurring blocks

ValueCountFrequency (%)
ASCII 165839
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
a 14421
 
8.7%
e 13778
 
8.3%
- 11370
 
6.9%
/ 10575
 
6.4%
r 9673
 
5.8%
n 8390
 
5.1%
s 7729
 
4.7%
i 6498
 
3.9%
o 5434
 
3.3%
d 5056
 
3.0%
Other values (58) 72915
44.0%

image
Text

UNIQUE 

Distinct2115
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size97.6 KiB
2023-07-27T12:28:39.530650image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Length

Max length140
Median length124
Mean length100.45674
Min length69

Characters and Unicode

Total characters212466
Distinct characters72
Distinct categories7 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique2115 ?
Unique (%)100.0%

Sample

1st rowhttps://cdn.parfumdreams.de/Img/Art/13/Hugo-Boss-BOSS-Bottled-Eau-de-Toilette-Spray-12855_26.jpg
2nd rowhttps://cdn.parfumdreams.de/Img/Art/13/Yves-Saint-Laurent-Y-Eau-de-Parfum-Spray-79931_22.jpg
3rd rowhttps://cdn.parfumdreams.de/Img/Art/13/Abercrombie-Fitch-Away-Weekend-Men-Eau-de-Toilette-Spray-123613_4.jpg
4th rowhttps://cdn.parfumdreams.de/Img/Art/13/Jean-Paul-Gaultier-Le-Male-Eau-de-Toilette-Spray-17304_31.jpg
5th rowhttps://cdn.parfumdreams.de/Img/Art/13/DIOR-Sauvage-Eau-de-Parfum-Spray-74836x8_81.jpg
ValueCountFrequency (%)
https://cdn.parfumdreams.de/img/art/13/hugo-boss-boss-bottled-eau-de-toilette-spray-12855_26.jpg 1
 
< 0.1%
https://cdn.parfumdreams.de/img/art/13/dior-fahrenheit-le-parfum-spray-44912_2.jpg 1
 
< 0.1%
https://cdn.parfumdreams.de/img/art/13/abercrombie-fitch-away-weekend-men-eau-de-toilette-spray-123613_4.jpg 1
 
< 0.1%
https://cdn.parfumdreams.de/img/art/13/jean-paul-gaultier-le-male-eau-de-toilette-spray-17304_31.jpg 1
 
< 0.1%
https://cdn.parfumdreams.de/img/art/13/dior-sauvage-eau-de-parfum-spray-74836x8_81.jpg 1
 
< 0.1%
https://cdn.parfumdreams.de/img/art/13/jil-sander-sun-men-eau-de-toilette-spray-17427x1_4.jpg 1
 
< 0.1%
https://cdn.parfumdreams.de/img/art/13/gisada-ambassador-for-men-eau-de-parfum-spray-94968.jpg 1
 
< 0.1%
https://cdn.parfumdreams.de/img/art/13/paco-rabanne-1-million-eau-de-toilette-spray-13455x3_64.jpg 1
 
< 0.1%
https://cdn.parfumdreams.de/img/art/13/paco-rabanne-1-million-parfum-spray-90243_57.jpg 1
 
< 0.1%
https://cdn.parfumdreams.de/img/art/13/creed-aventus-eau-de-parfum-spray-29150_7.jpg 1
 
< 0.1%
Other values (2105) 2105
99.5%
2023-07-27T12:28:40.025448image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
- 17850
 
8.4%
a 13855
 
6.5%
e 13345
 
6.3%
r 13134
 
6.2%
/ 12690
 
6.0%
t 9964
 
4.7%
d 9614
 
4.5%
m 9036
 
4.3%
p 8611
 
4.1%
u 7365
 
3.5%
Other values (62) 97002
45.7%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 131755
62.0%
Uppercase Letter 22811
 
10.7%
Other Punctuation 21173
 
10.0%
Dash Punctuation 17850
 
8.4%
Decimal Number 17792
 
8.4%
Connector Punctuation 1083
 
0.5%
Currency Symbol 2
 
< 0.1%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
a 13855
 
10.5%
e 13345
 
10.1%
r 13134
 
10.0%
t 9964
 
7.6%
d 9614
 
7.3%
m 9036
 
6.9%
p 8611
 
6.5%
u 7365
 
5.6%
s 6663
 
5.1%
n 5363
 
4.1%
Other values (18) 34805
26.4%
Uppercase Letter
ValueCountFrequency (%)
E 2886
12.7%
A 2883
12.6%
I 2735
12.0%
S 2569
11.3%
P 2075
9.1%
T 1084
 
4.8%
C 1047
 
4.6%
M 939
 
4.1%
L 734
 
3.2%
B 703
 
3.1%
Other values (16) 5156
22.6%
Decimal Number
ValueCountFrequency (%)
1 5189
29.2%
3 3282
18.4%
2 1499
 
8.4%
9 1197
 
6.7%
4 1188
 
6.7%
6 1164
 
6.5%
8 1132
 
6.4%
0 1107
 
6.2%
7 1061
 
6.0%
5 973
 
5.5%
Other Punctuation
ValueCountFrequency (%)
/ 12690
59.9%
. 6345
30.0%
: 2115
 
10.0%
! 19
 
0.1%
, 4
 
< 0.1%
Dash Punctuation
ValueCountFrequency (%)
- 17850
100.0%
Connector Punctuation
ValueCountFrequency (%)
_ 1083
100.0%
Currency Symbol
ValueCountFrequency (%)
$ 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 154566
72.7%
Common 57900
 
27.3%

Most frequent character per script

Latin
ValueCountFrequency (%)
a 13855
 
9.0%
e 13345
 
8.6%
r 13134
 
8.5%
t 9964
 
6.4%
d 9614
 
6.2%
m 9036
 
5.8%
p 8611
 
5.6%
u 7365
 
4.8%
s 6663
 
4.3%
n 5363
 
3.5%
Other values (44) 57616
37.3%
Common
ValueCountFrequency (%)
- 17850
30.8%
/ 12690
21.9%
. 6345
 
11.0%
1 5189
 
9.0%
3 3282
 
5.7%
: 2115
 
3.7%
2 1499
 
2.6%
9 1197
 
2.1%
4 1188
 
2.1%
6 1164
 
2.0%
Other values (8) 5381
 
9.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 212464
> 99.9%
None 2
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
- 17850
 
8.4%
a 13855
 
6.5%
e 13345
 
6.3%
r 13134
 
6.2%
/ 12690
 
6.0%
t 9964
 
4.7%
d 9614
 
4.5%
m 9036
 
4.3%
p 8611
 
4.1%
u 7365
 
3.5%
Other values (60) 97000
45.7%
None
ValueCountFrequency (%)
Å“ 1
50.0%
Å¡ 1
50.0%

Interactions

2023-07-27T12:28:27.769165image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-27T12:28:07.059901image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-27T12:28:20.624533image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-27T12:28:24.248887image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-27T12:28:30.664211image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-27T12:28:12.919599image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-27T12:28:23.831773image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-27T12:28:27.315125image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-27T12:28:30.801069image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-27T12:28:15.659635image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-27T12:28:23.962001image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-27T12:28:27.482454image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-27T12:28:30.921143image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-27T12:28:18.344054image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-27T12:28:24.103850image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-27T12:28:27.621682image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Correlations

2023-07-27T12:28:40.182483image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
perfume_idbase_pricecustomer_ratingreview_countcategorygenderfragrance
perfume_id1.0000.1160.1540.1131.0001.0001.000
base_price0.1161.000-0.118-0.1770.2970.2790.118
customer_rating0.154-0.1181.0000.6950.1110.2400.131
review_count0.113-0.1770.6951.0000.0000.0340.103
category1.0000.2970.1110.0001.0000.3200.121
gender1.0000.2790.2400.0340.3201.0000.452
fragrance1.0000.1180.1310.1030.1210.4521.000

Missing values

2023-07-27T12:28:31.146959image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
A simple visualization of nullity by column.
2023-07-27T12:28:31.560486image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
Nullity matrix is a data-dense display which lets you quickly visually pick out patterns in data completion.
2023-07-27T12:28:31.835364image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
The correlation heatmap measures nullity correlation: how strongly the presence or absence of one variable affects the presence of another.

Sample

perfume_idbrandnamecategorygenderbase_pricenotestop_noteheart_notebase_notefragrancecustomer_ratingreview_counturlimage
012855Hugo BossBOSS BottledEau de ToiletteMen739.00apple, bergamot, lemon, geranium, carnation, cinnamon, sandalwood, vetiver, cedarapple, bergamot, lemongeranium, carnation, cinnamonsandalwood, vetiver, cedarNaN4.9144/Hugo-Boss/Boss-Black-Mens-fragrances/BOSS-Bottled/Eau-de-Toilette-Spray/index_12855.aspxhttps://cdn.parfumdreams.de/Img/Art/13/Hugo-Boss-BOSS-Bottled-Eau-de-Toilette-Spray-12855_26.jpg
179931Yves Saint LaurentYEau de ParfumMen915.83apple, bergamot, ginger, geranium, mint, sage, juniper berry, amber, tonka bean, incenseapple, bergamot, gingergeranium, mint, sage, juniper berryamber, tonka bean, incenseNaN4.9137/Yves-Saint-Laurent/Mens-fragrances/Y/Eau-de-Parfum-Spray/index_79931.aspxhttps://cdn.parfumdreams.de/Img/Art/13/Yves-Saint-Laurent-Y-Eau-de-Parfum-Spray-79931_22.jpg
2123613Abercrombie & FitchAway Weekend MenEau de ToiletteMen1398.33bergamot, cardamom, mandarin, lavender, rosemary, sage, cocoa, patchouli, cedar woodbergamot, cardamom, mandarinlavender, rosemary, sagecocoa, patchouli, cedar woodNaN0.00/Abercrombie-Fitch/Mens-fragrances/Away-Weekend-Men/Eau-de-Toilette-Spray/index_123613.aspxhttps://cdn.parfumdreams.de/Img/Art/13/Abercrombie-Fitch-Away-Weekend-Men-Eau-de-Toilette-Spray-123613_4.jpg
317304Jean Paul GaultierLe MâleEau de ToiletteMen923.75bergamot, lavender, mint, spices, orange, cinnamon, amber, sandalwood, tonka beanbergamot, lavender, mintspices, orange, cinnamonamber, sandalwood, tonka beanNaN4.9275/Jean-Paul-Gaultier/Mens-fragrances/Le-Male/Eau-de-Toilette-Spray/index_17304.aspxhttps://cdn.parfumdreams.de/Img/Art/13/Jean-Paul-Gaultier-Le-Male-Eau-de-Toilette-Spray-17304_31.jpg
474836DIORSauvage Citrus and Vanilla NotesEau de ParfumMen2231.67bergamot, lavender, pepper, amber, patchouli, vetiverbergamot, lavenderpepperamber, patchouli, vetiverwooden4.9156/DIOR/Mens-fragrances/Sauvage/Eau-de-Parfum-Spray/index_74836.aspxhttps://cdn.parfumdreams.de/Img/Art/13/DIOR-Sauvage-Eau-de-Parfum-Spray-74836x8_81.jpg
617427Jil SanderSun MenEau de ToiletteMen698.75bergamot, cascalone, rosemary, flowers, cardamom, nutmeg, amber, musk, sandalwoodbergamot, cascalone, rosemaryflowers, cardamom, nutmegamber, musk, sandalwoodwooden4.7266/Jil-Sander/Mens-fragrances/Sun-Men/Eau-de-Toilette-Spray/index_17427.aspxhttps://cdn.parfumdreams.de/Img/Art/13/Jil-Sander-Sun-Men-Eau-de-Toilette-Spray-17427x1_4.jpg
894968GisadaAmbassador For MenEau de ParfumMen1579.00apple, green notes, cardamom, mandarin, violet, lavender, mango, patchouli, pepper, peony, amber, wood, moss, vanilla, vetiverapple, green notes, cardamom, mandarin, violetlavender, mango, patchouli, pepper, peonyamber, wood, moss, vanilla, vetiveroriental4.9134/Gisada/Mens-fragrances/Ambassador-For-Men/Eau-de-Parfum-Spray/index_94968.aspxhttps://cdn.parfumdreams.de/Img/Art/13/Gisada-Ambassador-For-Men-Eau-de-Parfum-Spray-94968.jpg
913455Paco Rabanne1 MillionEau de ToiletteMen1279.00grapefruit, mint, spices, rose, cinnamon, wood, leather, patchouli, styraxgrapefruit, mintspices, rose, cinnamonwood, leather, patchouli, styraxNaN4.9268/Paco-Rabanne/Mens-fragrances/1-Million/Eau-de-Toilette-Spray/index_13455.aspxhttps://cdn.parfumdreams.de/Img/Art/13/Paco-Rabanne-1-Million-Eau-de-Toilette-Spray-13455x3_64.jpg
1090243Paco Rabanne1 MillionParfumMen979.00grapefruit, mint, spices, rose, cinnamon, wood, leather, patchouli, styraxgrapefruit, mintspices, rose, cinnamonwood, leather, patchouli, styraxNaN4.894/Paco-Rabanne/Mens-fragrances/1-Million/Parfum-Spray/index_90243.aspxhttps://cdn.parfumdreams.de/Img/Art/13/Paco-Rabanne-1-Million-Parfum-Spray-90243_57.jpg
1129150CreedAventusEau de ParfumMen4200.00pineapple, apple, bergamot, jasmine, patchouli, rose, amber, musk, vanillapineapple, apple, bergamotjasmine, patchouli, roseamber, musk, vanillaNaN4.576/Creed/Mens-fragrances/Aventus/Eau-de-Parfum-Spray/index_29150.aspxhttps://cdn.parfumdreams.de/Img/Art/13/Creed-Aventus-Eau-de-Parfum-Spray-29150_7.jpg
perfume_idbrandnamecategorygenderbase_pricenotestop_noteheart_notebase_notefragrancecustomer_ratingreview_counturlimage
3214122211Clive ChristianCrown Collection Town & CountryEau de ParfumUnisex9000.00bergamot, clary sage, lemon, wacholder, cardamom, sandalwood, tea, olibanum, amber, patchouli, cashmere, cedar woodbergamot, clary sage, lemon, wacholdercardamom, sandalwood, tea, olibanumamber, patchouli, cashmere, cedar woodNaN0.00/Clive-Christian/Collections/Crown-Collection/Eau-de-Parfum-Spray/index_122211.aspxhttps://cdn.parfumdreams.de/Img/Art/13/Clive-Christian-Crown-Collection-Town-Country-Eau-de-Parfum-Spray-122211.jpg
3216115129Pana Dora SwedenXVIEau de ParfumUnisex2799.50bergamot, vermouth, herbs, balsam, caraway, labdanum, nagarmotha, patchouli, incense, wacholder, guaiac woodbergamot, vermouthherbsbalsam, caraway, labdanum, nagarmotha, patchouli, incense, wacholder, guaiac woodNaN0.00/Pana-Dora-Sweden/Unisexduefte/XVI/Eau-de-Parfum-Spray/index_115129.aspxhttps://cdn.parfumdreams.de/Img/Art/13/Pana-Dora-Sweden-XVI-Eau-de-Parfum-Spray-115129.jpg
321759606Perris Monte CarloExtraits de ParfumParfumUnisex5699.00geranium, lemon, nutmeg, rose, muskgeranium, lemon, nutmegrosemusk, rosefloral5.01/Perris-Monte-Carlo/Collection/Extraits-de-Parfum/Extrait/index_59606.aspxhttps://cdn.parfumdreams.de/Img/Art/13/Perris-Monte-Carlo-Rose-de-Taif-Extrait-59606.jpg
321839814MontaleOud Aoud SafranEau de ParfumUnisex1250.00cardamom, carnation, saffron, jasmine, oud, patchouli, rose, oakmoss, leather, musk, sandalwoodcardamom, carnation, saffronjasmine, oud, patchouli, roseoakmoss, leather, musk, sandalwoodNaN5.01/Montale/Fragrances/Oud/Eau-de-Parfum-Spray/index_39814.aspxhttps://cdn.parfumdreams.de/Img/Art/13/Montale-Oud-Aoud-Safran-Eau-de-Parfum-Spray-39814_1.jpg
3221105845MEMO ParisGraines Vagabondes CorfuEau de ParfumUnisex2452.67bergamot, cassis, grapefruit, mandarin, lemon, geranium, jasmine, lily of the valley, peach, amber, moss, musk, patchouli, sandalwood, cedarbergamot, cassis, grapefruit, mandarin, lemongeranium, jasmine, lily of the valley, peachamber, moss, musk, patchouli, sandalwood, cedarNaN0.00/MEMO-Paris/Collections/Graines-Vagabondes/Eau-de-Parfum-Spray/index_105845.aspxhttps://cdn.parfumdreams.de/Img/Art/13/MEMO-Paris-Graines-Vagabondes-Corfu-Eau-de-Parfum-Spray-105845.jpg
3222112366INITIO Parfums PrivésBlack Gold Project Oud For HappinessEau de ParfumUnisex3277.22bergamot, ginger, musk, oud, vanilla, herbs, cedar wood, liquoricebergamot, ginger, musk, oud, vanilla, herbs, cedar woodbergamot, ginger, musk, oud, vanilla, herbs, liquorice, cedar woodginger, musk, oud, vanilla, bergamot, herbs, liquorice, cedar woodNaN0.00/INITIO-Parfums-Prives/Collections/Black-Gold-Project/Eau-de-Parfum-Spray/index_112366.aspxhttps://cdn.parfumdreams.de/Img/Art/13/INITIO-Parfums-Prives-Black-Gold-Project-Oud-For-Happiness-Eau-de-Parfum-Spray-112366.jpg
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322562011AetherCitrus EsterEau de ParfumUnisex1499.50grapefruit, fruity notes, rhubarbgrapefruit, fruity notesrhubarb, fruity notesNaNfruity5.01/Aether/Unisex-fragrances/Citrus-Ester/Eau-de-Parfum-Spray/index_62011.aspxhttps://cdn.parfumdreams.de/Img/Art/13/Aether-Citrus-Ester-Eau-de-Parfum-Spray-62011.jpg
322639758MontaleSea SandflowersEau de ParfumUnisex1050.00algae, salt, aquatic notes, spices, juniper berry, oakmoss, sandalwoodalgae, salt, aquatic notesspices, juniper berryoakmoss, sandalwoodNaN5.02/Montale/Fragrances/Sea/Eau-de-Parfum-Spray/index_39758.aspxhttps://cdn.parfumdreams.de/Img/Art/13/Montale-Sea-Sandflowers-Eau-de-Parfum-Spray-39758_1.jpg
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